Abstract
The fight against the COVID-19 pandemic still involves many struggles and challenges. The greatest challenge that most governments are currently facing is the lack of a precise, accurate, and automated mechanism for detecting and tracking new COVID-19 cases. In response to this challenge, this study proposes the first blockchain-based system, called the COVID-19 contact tracing system (CCTS), to verify, track, and detect new cases of COVID-19. The proposed system consists of four integrated components: an infection verifier subsystem, a mass surveillance subsystem, a P2P mobile application, and a blockchain platform for managing all transactions between the three subsystem models. To investigate the performance of the proposed system, CCTS has been simulated and tested against a created dataset consisting of 300 confirmed cases and 2539 contacts. Based on the metrics of the confusion matrix (i.e., recall, precision, accuracy, and F1 Score), the detection evaluation results proved that the proposed blockchain-based system achieved an average of accuracy of 75.79% and a false discovery rate (FDR) of 0.004 in recognizing persons in contact with COVID-19 patients within two different areas of infection covered by GPS. Moreover, the simulation results also demonstrated the success of the proposed system in performing self-estimation of infection probabilities and sending and receiving infection alerts in P2P communications in crowds of people by users. The infection probability results have been calculated using the binomial distribution function technique. This result can be considered unique compared with other similar systems in the literature. The new system could support governments, health authorities, and citizens in making critical decisions regarding infection detection, prediction, tracking, and avoiding the COVID-19 outbreak. Moreover, the functionality of the proposed CCTS can be adapted to work against any other similar pandemics in the future.
Highlights
The world is currently witnessing a dangerous transformation of the COVID-19 pandemic, rapidly threatening peoples’ lives and the global economy amid fears of sequential waves and genetic mutations of this pandemic
After simulating the proposed contact tracing system (CCTS)’s functionality on 2539 contacts distributed evenly across each confirmed COVID-19-case, each confirmed case has n contact persons within a 2 m2 area covered by the GPS
The results proved that the wider the GPS area is, the more accurate CCTS is in detecting contacts of COVID-19
Summary
The world is currently witnessing a dangerous transformation of the COVID-19 pandemic, rapidly threatening peoples’ lives and the global economy amid fears of sequential waves and genetic mutations of this pandemic. There is widespread agreement among economists that this pandemic will have substantial negative impacts on the global economy that extend to 2022. According to Statista, the global economy lost at least 2.4% of its gross domestic product (GDP) in 2020. In 2019, the global GDP was estimated at approximately 86.6 trillion US dollars, meaning that just a 6% drop in economic growth amounts to almost 3.5 trillion US dollars in lost economic output [2]. Despite the small increase in optimism with the decrease in the number of infected people in some countries and the approach of vaccine production, a resurgence of COVID-19 in 2021 could leave economies suffering in subsequent years and negate all efforts made to fight against its spread
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